Radial basis function methods for interpolation can be interpreted as roughness-minimizing splines. Although this relationship has already been established for radial basis functions of the form g(r) = r and g(r) = r log(r), it is extended here to include a much larger class of functions. This class includes the multiquadric g(r) = (r 2 + c 2) 1=2 and inverse multiquadric g(r) = (r 2 + c 2) ?1=...

Promising numerical results using once and twice integrated radial basis functions have been recently presented. In this work we investigate the integrated radial basis function (IRBF) concept in greater detail, connect to the existing RBF theory, and make conjectures about the properties of IRBF approximation methods. The IRBF methods are used to solve PDEs. c © 2006 Elsevier Science Ltd. All ...

Recently, a new class of surface-divergence free radial basis function interpolants has been developed for surfaces in R3. In this paper, several approximation results for this class of interpolants will be derived in the case of the sphere, S2. In particular, Sobolev-type error estimates are obtained, as well as optimal stability estimates for the associated interpolation matrices. In addition...

It is known that interpolation with radial basis functions of the same shape can guarantee a non-singular interpolation matrix, whereas little is known when one uses various shapes. In this paper, we prove that a class of compactly supported radial basis functions are convex on a certain region; based on this local convexity and ready local geometrical property of the interpolation points, we c...

A new projection method based on radial basis functions (RBFs) is presented for discretizing the incompressible unsteady Stokes equations in irregular geometries. The novelty of the method comes from the application of a new technique for computing the Leray-Helmholtz projection of a vector field using generalized interpolation with divergence-free and curl-free RBFs. Unlike traditional project...

The U.S. National Hurricane Center (NHC) issues advisories every six hours during the life of a hurricane. These advisories describe the current state of the storm, and its predicted path, size, and wind speed over the next five days. However, from these data alone, the question “What is the likelihood that the storm will hit Houston with hurricane strength winds between 12:00 and 14:00 on Satu...

The use of radial basis functions have attracted increasing attention in recent years as an elegant scheme for high-dimensional scattered data approximation, an accepted method for machine learning, one of the foundations of mesh-free methods, an alternative way to construct higher order methods for solving partial differential equations (PDEs), an emerging method for solving PDEs on surfaces, ...

We generalize techniques dating back to Duchon 4] for error estimates for interpolation by thin plate splines to basis functions with positive and algebraically decaying Fourier transform. We include L p-estimates for 1 p < 2 that can also be applied to thin plate spline approximation. x1. Introduction Radial basis functions are a well-established tool for multivariate approximation problems. A...

This paper connects two thoroughly investigated universal approximator techniques to each other. Recently, it has been shown that the input-output function of the general fuzzy KH interpolation method [1, 2] as well as its modification [3] are stable in the mathematical sense, or in other words, they can be considered as universal approximators with respect to the Lp (p ∈ [1,∞]) norm in the spa...

The paper deals with Div-Curl approximation problem by weighted thin plate splines. The weighted thin plate splines are an extension of the well known thin plate splines and are radial basis functions which allow the approximation and interpolation of a scalar functions from a given scattered data. We show how the weighted thin plate splines may also be used for the approximation and interpolat...